Next Article in Journal
Enhanced Prognostic Model for Lithium Ion Batteries Based on Particle Filter State Transition Model Modification
Next Article in Special Issue
Elastic Stability of Perforated Plates Strengthened with FRP under Uniaxial Compression
Previous Article in Journal
Modified Local Linear Embedding Algorithm for Rolling Element Bearing Fault Diagnosis
Previous Article in Special Issue
Hybrid Prediction Model of the Temperature Field of a Motorized Spindle
Article Menu
Issue 11 (November) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(11), 1179; https://doi.org/10.3390/app7111179

Determination of the Constants of GTN Damage Model Using Experiment, Polynomial Regression and Kriging Methods

1
Mechanical Engineering Department, Bu-Ali Sina University, Hamedan 6517838695, Iran
2
Mechanical and Aerospace Engineering Department, Politecnico di Torino, Torino 10129, Italy
3
Mechanical Engineering Department, University of Texas at Arlington, Arlington, TX 76019, USA
*
Author to whom correspondence should be addressed.
Received: 8 October 2017 / Revised: 9 November 2017 / Accepted: 10 November 2017 / Published: 15 November 2017
(This article belongs to the Special Issue Soft Computing Techniques in Structural Engineering and Materials)
Full-Text   |   PDF [6788 KB, uploaded 16 November 2017]   |  

Abstract

Damage models, particularly the Gurson–Tvergaard–Needleman (GTN) model, are widely used in numerical simulation of material deformations. Each damage model has some constants which must be identified for each material. The direct identification methods are costly and time consuming. In the current work, a combination of experimental, numerical simulation and optimization were used to determine the constants. Quasi-static and dynamic tests were carried out on notched specimens. The experimental profiles of the specimens were used to determine the constants. The constants of GTN damage model were identified through the proposed method and using the results of quasi-static tests. Numerical simulation of the dynamic test was performed utilizing the constants obtained from quasi-static experiments. The results showed a high precision in predicting the specimen’s profile in the dynamic testing. The sensitivity analysis was performed on the constants of GTN model to validate the proposed method. Finally, the experiments were simulated using the Johnson–Cook (J–C) damage model and the results were compared to those obtained from GTN damage model. View Full-Text
Keywords: damage model; Gurson model; Kriging method; simulation; optimization damage model; Gurson model; Kriging method; simulation; optimization
Figures

Graphical abstract

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Rahimidehgolan, F.; Majzoobi, G.; Alinejad, F.; Fathi Sola, J. Determination of the Constants of GTN Damage Model Using Experiment, Polynomial Regression and Kriging Methods. Appl. Sci. 2017, 7, 1179.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top